Applying PageRank to a topic hierarchy tree(using SPARQL query extracted from DBpedia)

Question

As I have a DBpedia query and I want to rank those results by using the PageRank algorithm.

Toward the concept "Machine_learning", by using the SPARQL query below, I can find out all the ParentNodes, ChildNodes and SiblingNodes in DBpedia.

select * where {
{ ?childNodes skos:broader <http://dbpedia.org/resource/Category:Machine_learning> . ?childNodes skos:broader ?siblingConceptsFormChildNodes}
UNION
{<http://dbpedia.org/resource/Category:Machine_learning> skos:broader ?parentNodes . ?siblingConceptsFormParentNodes skos:broader ?parentNodes}
}

For the visualization, the topic hierarchy would be like this: Regulated concept map

As you may found that the topic hierarchy is based on the SKOS:broader and SKOS:narrower properties.

My intention is to rank all the nodes exist in the topic hierarchy by PageRank. The results from the query above are limited.

And I also found out this question that seems related to my question: How to use DBpedia properties to build a topic hierarchy?

However, I think the approach between us is a bit different.

I also adjust the PageRank algorithm for the topic hierarchy above:

PageRank algorithm

Thank you in advance!

Answer 1

If you have not already solved your problem, you might consider loading the DBpedia data into Anzograph and then using the built-in service. See docs and examples here https://docs.cambridgesemantics.com/anzograph/v2.2/userdoc/pagerank.htm

Disclaimer: I work for Cambridge Semantics Inc.